Articles | Volume 9, issue 8
https://doi.org/10.5194/wes-9-1689-2024
https://doi.org/10.5194/wes-9-1689-2024
Brief communication
 | 
15 Aug 2024
Brief communication |  | 15 Aug 2024

Brief communication: A simple axial induction modification to the Weather Research and Forecasting Fitch wind farm parameterization

Lukas Vollmer, Balthazar Arnoldus Maria Sengers, and Martin Dörenkämper

Related authors

An investigation of spatial wind direction variability and its consideration in engineering models
Anna von Brandis, Gabriele Centurelli, Jonas Schmidt, Lukas Vollmer, Bughsin' Djath, and Martin Dörenkämper
Wind Energ. Sci., 8, 589–606, https://doi.org/10.5194/wes-8-589-2023,https://doi.org/10.5194/wes-8-589-2023, 2023
Short summary
FarmConners wind farm flow control benchmark – Part 1: Blind test results
Tuhfe Göçmen, Filippo Campagnolo, Thomas Duc, Irene Eguinoa, Søren Juhl Andersen, Vlaho Petrović, Lejla Imširović, Robert Braunbehrens, Jaime Liew, Mads Baungaard, Maarten Paul van der Laan, Guowei Qian, Maria Aparicio-Sanchez, Rubén González-Lope, Vinit V. Dighe, Marcus Becker, Maarten J. van den Broek, Jan-Willem van Wingerden, Adam Stock, Matthew Cole, Renzo Ruisi, Ervin Bossanyi, Niklas Requate, Simon Strnad, Jonas Schmidt, Lukas Vollmer, Ishaan Sood, and Johan Meyers
Wind Energ. Sci., 7, 1791–1825, https://doi.org/10.5194/wes-7-1791-2022,https://doi.org/10.5194/wes-7-1791-2022, 2022
Short summary
Overview of the PALM model system 6.0
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020,https://doi.org/10.5194/gmd-13-1335-2020, 2020
Short summary
Transient LES of an offshore wind turbine
Lukas Vollmer, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 2, 603–614, https://doi.org/10.5194/wes-2-603-2017,https://doi.org/10.5194/wes-2-603-2017, 2017
Short summary
Stochastic Wake Modeling Based on POD Analysis
David Bastine, Lukas Vollmer, Matthias Wächter, and Joachim Peinke
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2016-38,https://doi.org/10.5194/wes-2016-38, 2016
Revised manuscript not accepted
Short summary

Related subject area

Thematic area: Wind and the atmosphere | Topic: Wind and turbulence
Underestimation of strong wind speeds offshore in ERA5: evidence, discussion and correction
Rémi Gandoin and Jorge Garza
Wind Energ. Sci., 9, 1727–1745, https://doi.org/10.5194/wes-9-1727-2024,https://doi.org/10.5194/wes-9-1727-2024, 2024
Short summary
Impact of swell waves on atmospheric surface turbulence: wave–turbulence decomposition methods
Mostafa Bakhoday Paskyabi
Wind Energ. Sci., 9, 1631–1645, https://doi.org/10.5194/wes-9-1631-2024,https://doi.org/10.5194/wes-9-1631-2024, 2024
Short summary
Machine-learning-based estimate of the wind speed over complex terrain using the long short-term memory (LSTM) recurrent neural network
Cássia Maria Leme Beu and Eduardo Landulfo
Wind Energ. Sci., 9, 1431–1450, https://doi.org/10.5194/wes-9-1431-2024,https://doi.org/10.5194/wes-9-1431-2024, 2024
Short summary
Method to predict the minimum measurement and experiment durations needed to achieve converged and significant results in a wind energy field experiment
Daniel R. Houck, Nathaniel B. de Velder, David C. Maniaci, and Brent C. Houchens
Wind Energ. Sci., 9, 1189–1209, https://doi.org/10.5194/wes-9-1189-2024,https://doi.org/10.5194/wes-9-1189-2024, 2024
Short summary
Experimental Evaluation of Wind Turbine Wake Turbulence Impacts on a General Aviation Aircraft
Jonathan Rogers
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-51,https://doi.org/10.5194/wes-2024-51, 2024
Revised manuscript accepted for WES
Short summary

Cited articles

Abkar, M. and Porté-Agel, F.: A new wind-farm parameterization for large-scale atmospheric models, J. Renew. Sustain. Energ., 7, 013121, https://doi.org/10.1063/1.4907600, 2015. a
Archer, C., Wu, S., Ma, Y., and Jimenez, P.: Two Corrections for Turbulent Kinetic Energy Generated by Wind Farms in the WRF Model, Mon. Weather Rev., 148, 4823–4835, https://doi.org/10.1175/MWR-D-20-0097.1, 2020. a
Cañadillas, B., Beckenbauer, M., Trujillo, J. J., Dörenkämper, M., Foreman, R., Neumann, T., and Lampert, A.: Offshore wind farm cluster wakes as observed by long-range-scanning wind lidar measurements and mesoscale modeling, Wind Energ. Sci., 7, 1241–1262, https://doi.org/10.5194/wes-7-1241-2022, 2022. a, b
Fischereit, J., Brown, R., Larsén, X. G., Badger, J., and Hawkes, G.: Review of Mesoscale Wind-Farm Parametrizations and Their Applications, Bound.-Lay. Meteorol., 182, 175–224, https://doi.org/10.1007/s10546-021-00652-y, 2021. a, b, c
Fitch, A. C., Olson, J. B., Lundquist, J. K., Dudhia, J., Gupta, A. K., Michalakes, J., and Barstad, I.: Local and Mesoscale Impacts of Wind Farms as Parameterized in a Mesoscale NWP Model, Mon. Weather Rev., 140, 3017–3038, https://doi.org/10.1175/MWR-D-11-00352.1, 2012. a
Download
Short summary
This study proposes a modification to a well-established wind farm parameterization used in mesoscale models. The wind speed at the location of the turbine, which is used to calculate power and thrust, is corrected to approximate the free wind speed. Results show that the modified parameterization produces more accurate estimates of the turbine’s power curve.
Altmetrics
Final-revised paper
Preprint